Evaluation of ERA-20cm reanalysis dataset over South Korea

Kim Dong-Ik, Dawei Han

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)
81 Downloads (Pure)


Long term climate data are key in assessing water related hazards in order to adapt and mitigate climate change. Reanalysis has been developed as a surrogate for local observations, but there is a lack of studies about the suitability at different parts of the world. In this study, our primary goal of this study was to identify the applicability of the ECMWF 20th century atmospheric model ensemble (ERA-20cm) in South Korea. Thus, we have evaluated the ensemble for precipitation and temperature by assessing the correlation coefficients, the long-term trend by the Mann-Kendall test, the skill score based on the probability density functions (PDFs) and the goodness of the ensemble spread. The relationship between the spread and the El Niño-Southern Oscillation (ENSO) has also been explored. ERA-20cm ensemble has difficulty in providing useful information on the long term trend as well as the temporal variability in South Korea, but, for the pdf-based comparison, all ensemble predictions represent significant agreements. It is found that the ensemble mean can misrepresent ten individual members, especially for statistical estimates, in regional-scale analyses. The ensemble does not spread well enough to cover the observation and there is no relationship between the spread and ENSO. This paper shows that the applicability of ERA-20cm may vary by region, hence these findings help to fill in the knowledge gaps about the applicability of the reanalysis in regional scale study including South Korea.

Original languageEnglish
Pages (from-to)10-24
Number of pages15
JournalJournal of Hydro-environment Research
Early online date23 Jan 2019
Publication statusPublished - Mar 2019

Structured keywords

  • Water and Environmental Engineering


  • ERA-20cm
  • interannual variability
  • non-parametric trend test
  • skill score
  • reanalysis


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